Spurious correlation #5,462 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Karen and the second variable is Air pollution in Atlantic City, New Jersey. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Karen and the second variable is Air pollution in Atlantic City, New Jersey. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As fewer babies were named Karen, there was a decrease in demand for personalized novelty license plates. This led to a reduction in the production and transportation of these plates, ultimately decreasing overall air pollution in Atlantic City, New Jersey. With fewer Karen-themed souvenirs being made and sold, the air quality in the bustling boardwalk area improved.

^{Show image generation prompt} Model: dalle-3
Prompt: [ An image that looks like it is a scene from 'Star Wars' ] portraying a futuristic cityscape on the Atlantic City, New Jersey boardwalk. The scene features advanced technology and air-cleaning machines positioned among the bustling crowds to tackle air pollution. The buildings have a modern, sci-fi architecture with clean, futuristic lines. People are visible strolling along the boardwalk, while in the background, towering and gleaming air-purification towers stand, emitting a futuristic, blue-hued glow. The atmosphere is bright, sunny, and filled with a sense of hope for a cleaner, fresher environment. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: 3D Pixar Style Celtic art A scene from Skyrim An image that looks like it is a scene from 'Star Wars' Low poly
ChatGPT: An image that looks like it is a scene from 'Star Wars'

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey, in the following situation: As fewer babies were named Karen, there was a decrease in demand for personalized novelty license plates. This led to a reduction in the production and transportation of these plates, ultimately decreasing overall air pollution in Atlantic City, New Jersey. With fewer Karen-themed souvenirs being made and sold, the air quality in the bustling boardwalk area improved.. Keep the description simple.
ChatGPT: In Atlantic City, New Jersey, the boardwalk was bustling with people enjoying the sunny day. Along the boardwalk, there were fewer stalls selling personalized novelty license plates with the name "Karen" on them. As a result, there were fewer delivery trucks transporting these souvenir plates, contributing to a decrease in air pollution. The air felt fresher as families strolled along the boardwalk, enjoying the cleaner environment.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In Atlantic City, New Jersey, the boardwalk was bustling with people enjoying the sunny day. Along the boardwalk, there were fewer stalls selling personalized novelty license plates with the name "Karen" on them. As a result, there were fewer delivery trucks transporting these souvenir plates, contributing to a decrease in air pollution. The air felt fresher as families strolled along the boardwalk, enjoying the cleaner environment. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ An image that looks like it is a scene from 'Star Wars' ] portraying a futuristic cityscape on the Atlantic City, New Jersey boardwalk. The scene features advanced technology and air-cleaning machines positioned among the bustling crowds to tackle air pollution. The buildings have a modern, sci-fi architecture with clean, futuristic lines. People are visible strolling along the boardwalk, while in the background, towering and gleaming air-purification towers stand, emitting a futuristic, blue-hued glow. The atmosphere is bright, sunny, and filled with a sense of hope for a cleaner, fresher environment.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Karen caused Air pollution in Atlantic City, New Jersey to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

The Journal of Environmental Quirks and Anomalies

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey. Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

[[ABSTRACT]]
This research presents a peculiar analysis of the correlation between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our study uncovers an unexpected relationship between the two seemingly unrelated variables. With a correlation coefficient of 0.9217117 and p < 0.01 from 1980 to 2022, the findings are truly a breath of fresh air in the field of name-based epidemiology and environmental science. Join us as we navigate the winds of change and unveil the curious connection between "Karen" and air pollution, shedding light on this lighthearted yet surprisingly robust association.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The relationship between human behavior and environmental factors has long been a subject of fascination and conjecture in the fields of epidemiology and environmental science. However, it is not every day that one comes across a connection as unexpected and, dare I say, whimsical, as the one between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. This study delves into the quirkier side of data analysis, where statistical correlations meet social nomenclature to uncover a most unusual relationship.
The first name "Karen" has been the subject of countless memes and jokes in recent years, often associated with a particular stereotype that has permeated popular culture. On the other hand, air pollution, though no laughing matter, has been a persistent environmental concern, especially in urban areas such as Atlantic City. The intersection of these seemingly disparate concepts forms the basis of our investigation.
As we embark on this intellectual escapade, it is imperative to maintain a lighthearted demeanor while interpreting the empirical observations. After all, what better way to spice up the usually somber discourse of air quality research than to introduce a dash of humor and whimsy, wouldn't you agree? The correlation coefficient and p-value may be high, but let us not forget the value of a good pun or two in the pursuit of knowledge!
Join us as we unravel the intrigue behind the "Karen" and air pollution affair, and strive to breathe new life into the world of name-based epidemiology and environmental science. The winds of curiosity are blowing, and we are ready to explore this unexpected and delightful association.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Smith et al. initiated the exploration of name-based epidemiology by examining the social and cultural implications of given names in their study "The Social Significance of Surnames." Meanwhile, Doe and Jones delved into the environmental factors affecting air quality in urban areas in their seminal work "The Urban Air Pollution Crisis." These foundational studies set the stage for our investigation into the connection between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey.

In "Name Power," the authors explore the influence of names on personal identity and social perceptions, laying the groundwork for our exploration of the implications of the name "Karen" in popular culture and its potential impact on environmental phenomena. Similarly, "Breathless in Atlantic City" by Environmentalist & Co. provides a comprehensive analysis of air pollution trends in Atlantic City, offering valuable insights into the environmental dynamics of this coastal metropolis.

Moving into the realm of fiction, "The Air Pollution Paradox" by Novelista del Mundo weaves a compelling narrative around the enigmatic relationship between urban air quality and human quirks, setting a tone that resonates with our present investigation. Furthermore, "Karen: A Name's Tale" by FictionFrenzy immerses readers in the captivating world of name-based peculiarities, hinting at the underlying parallels between social perceptions and environmental conditions.

On a more light-hearted note, the "Karen" meme phenomenon has permeated internet culture, making its mark on social media platforms and inspiring a plethora of comedic interpretations. The meme's widespread influence reflects the societal fascination with the name "Karen" and sets the stage for our attempt to unravel its surprising connection to air pollution in Atlantic City.

As we survey the eclectic landscape of literature and popular culture surrounding these seemingly incongruous topics, we are reminded of the boundless potential for unearthing unexpected correlations and whimsical associations in the pursuit of knowledge. The stage is set, and the spotlight is on the enthralling relationship between the first name Karen and air pollution in Atlantic City, promising an intellectual journey brimming with lighthearted intrigue and scholarly whimsy.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency . You used data from 1980 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

[[ABSTRACT]]
This research presents a peculiar analysis of the correlation between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our study uncovers an unexpected relationship between the two seemingly unrelated variables. With a correlation coefficient of 0.9217117 and p < 0.01 from 1980 to 2022, the findings are truly a breath of fresh air in the field of name-based epidemiology and environmental science. Join us as we navigate the winds of change and unveil the curious connection between "Karen" and air pollution, shedding light on this lighthearted yet surprisingly robust association.

[[INTRODUCTION]]
INTRODUCTION
The relationship between human behavior and environmental factors has long been a subject of fascination and conjecture in the fields of epidemiology and environmental science. However, it is not every day that one comes across a connection as unexpected and, dare I say, whimsical, as the one between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. This study delves into the quirkier side of data analysis, where statistical correlations meet social nomenclature to uncover a most unusual relationship.
The first name "Karen" has been the subject of countless memes and jokes in recent years, often associated with a particular stereotype that has permeated popular culture. On the other hand, air pollution, though no laughing matter, has been a persistent environmental concern, especially in urban areas such as Atlantic City. The intersection of these seemingly disparate concepts forms the basis of our investigation.
As we embark on this intellectual escapade, it is imperative to maintain a lighthearted demeanor while interpreting the empirical observations. After all, what better way to spice up the usually somber discourse of air quality research than to introduce a dash of humor and whimsy, wouldn't you agree? The correlation coefficient and p-value may be high, but let us not forget the value of a good pun or two in the pursuit of knowledge!
Join us as we unravel the intrigue behind the "Karen" and air pollution affair, and strive to breathe new life into the world of name-based epidemiology and environmental science. The winds of curiosity are blowing, and we are ready to explore this unexpected and delightful association.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The first step in unraveling the mystery behind the correlation between the first name "Karen" and air pollution levels in Atlantic City, New Jersey, involved a comprehensive data collection process. The research team scoured the depths of the internet, like intrepid explorers on a quest for truth, with a primary focus on obtaining data from reputable sources such as the US Social Security Administration and the Environmental Protection Agency. The years 1980 to 2022 were selected to capture the full spectrum of name popularity and air quality fluctuations, allowing us to paint a vivid picture of the relationship under investigation.

Name Popularity Measurement:
To quantify the popularity of the first name "Karen," the team delved into the vast archives of the US Social Security Administration, carefully extracting and analyzing the frequency of occurrences for each year within the designated time frame. Harnessing the power of statistical tools and database wizardry, we navigated the sea of data with the finesse of a seasoned mariner, ensuring a robust and precise measurement of the name's popularity.

Air Pollution Data Acquisition:
Turning our attention to the atmospheric realm, air pollution data for Atlantic City, New Jersey, was procured from the Environmental Protection Agency, serving as a crucial component in our analysis. By harnessing the arcane arts of environmental monitoring and data retrieval, we amassed a rich repository of air quality measurements, allowing us to gauge the ebb and flow of pollutants in the city's ethereal domain.

Statistical Analysis:
With our treasure trove of data in hand, we employed the venerable tools of correlation analysis to tease out the relationship between the popularity of the first name "Karen" and air pollution levels. Channeling the spirit of mathematical inquiry and statistical rigor, we calculated the correlation coefficient and p-value with the precision of an alchemist transmuting base metals into gold, unearthing the enchanting connection that bewitched our inquisitive minds.

Control Variables:
In our quest for scientific clarity, we scrupulously accounted for potential confounding variables, ensuring that our findings were not merely a mirage in the desert of statistical analysis. Factors such as demographic shifts, meteorological variations, and other environmental influences were subjected to rigorous scrutiny, guarding against the siren's call of spurious correlations and statistical chicanery.

Ethical Considerations:
As custodians of empirical inquiry, we upheld the principles of ethical research conduct, treating our data with the reverence befitting these venerable artifacts of knowledge. The privacy and integrity of individuals associated with the name "Karen" were safeguarded, honoring their anonymity amidst the ebbs and flows of statistical scrutiny, much like guardians of a fabled treasure, defending it from unwarranted intrusion.

In conclusion, our methodology represents a harmonious blend of meticulous data collection, statistical sorcery, and ethical vigilance, guiding us through the labyrinth of name-based epidemiology and environmental science. With our compass set to the winds of curiosity, we stand prepared to illuminate the enigmatic bond between "Karen" and air pollution, brimming with the spirit of intellectual adventure and a sprinkle of statistical stardust.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

[[ABSTRACT]]
This research presents a peculiar analysis of the correlation between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our study uncovers an unexpected relationship between the two seemingly unrelated variables. With a correlation coefficient of 0.9217117 and p < 0.01 from 1980 to 2022, the findings are truly a breath of fresh air in the field of name-based epidemiology and environmental science. Join us as we navigate the winds of change and unveil the curious connection between "Karen" and air pollution, shedding light on this lighthearted yet surprisingly robust association.

[[LITERATURE REVIEW]]
Smith et al. initiated the exploration of name-based epidemiology by examining the social and cultural implications of given names in their study "The Social Significance of Surnames." Meanwhile, Doe and Jones delved into the environmental factors affecting air quality in urban areas in their seminal work "The Urban Air Pollution Crisis." These foundational studies set the stage for our investigation into the connection between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey.
In "Name Power," the authors explore the influence of names on personal identity and social perceptions, laying the groundwork for our exploration of the implications of the name "Karen" in popular culture and its potential impact on environmental phenomena. Similarly, "Breathless in Atlantic City" by Environmentalist & Co. provides a comprehensive analysis of air pollution trends in Atlantic City, offering valuable insights into the environmental dynamics of this coastal metropolis.
Moving into the realm of fiction, "The Air Pollution Paradox" by Novelista del Mundo weaves a compelling narrative around the enigmatic relationship between urban air quality and human quirks, setting a tone that resonates with our present investigation. Furthermore, "Karen: A Name's Tale" by FictionFrenzy immerses readers in the captivating world of name-based peculiarities, hinting at the underlying parallels between social perceptions and environmental conditions.
On a more light-hearted note, the "Karen" meme phenomenon has permeated internet culture, making its mark on social media platforms and inspiring a plethora of comedic interpretations. The meme's widespread influence reflects the societal fascination with the name "Karen" and sets the stage for our attempt to unravel its surprising connection to air pollution in Atlantic City.
As we survey the eclectic landscape of literature and popular culture surrounding these seemingly incongruous topics, we are reminded of the boundless potential for unearthing unexpected correlations and whimsical associations in the pursuit of knowledge. The stage is set, and the spotlight is on the enthralling relationship between the first name Karen and air pollution in Atlantic City, promising an intellectual journey brimming with lighthearted intrigue and scholarly whimsy.

[[RESULTS]]
The results of our analysis revealed a remarkably strong correlation between the popularity of the first name Karen and air pollution in Atlantic City, New Jersey from 1980 to 2022. The correlation coefficient of 0.9217117 suggests a striking relationship, reminiscent of a chance encounter between a gust of wind and a tumbleweed in the desert of statistical probabilities.
With an r-squared value of 0.8495525, it is as if the data points aligned themselves with the precision of a synchronized swimming team, moving in perfect harmony to reveal this unlikely connection. The p-value of less than 0.01 indicates that the likelihood of this association being due to mere chance is about as probable as finding a polar bear in the Sahara desert.
Fig. 1 exhibits a scatterplot illustrating the robust association, with data points resembling constellations in the statistical galaxy, forging an unexpected constellation of "Karen" and air pollution. It is as if the data itself conspired to reveal this peculiar relationship, adding a touch of whimsy to the typically stern field of environmental science.
This unexpected correlation breathes new life into the realm of name-based epidemiology and environmental science, shining a light on the delightful and unconventional intersection between human nomenclature and air quality. It appears that in the arena of statistical peculiarities, the "Karen" and air pollution affair takes center stage, inviting further exploration and a touch of humor amidst the rigors of scientific inquiry.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study support the prior research that delved into the social and cultural implications of given names, as well as the environmental factors affecting air quality in urban areas. The lighthearted exploration of the "Karen" meme phenomenon in popular culture takes on a surprisingly robust dimension as we uncover the peculiar connection between the first name Karen and air pollution in Atlantic City, New Jersey.

The striking correlation coefficient of 0.9217117 observed in our analysis aligns with the literature suggesting the influence of names on personal identity and social perceptions. It appears that the name "Karen" has indeed left an indelible mark not only in popular culture but also in the environmental dynamics of Atlantic City, akin to a gust of wind leaving its imprint on the sand dunes of statistical relationships.

The robust r-squared value of 0.8495525 further echoes the precision of prior research that has explored the societal and cultural significance of given names. This statistical harmony between the popularity of the name "Karen" and air pollution levels in Atlantic City seems to play out like a perfectly choreographed dance, with each data point moving in tandem to form an unexpected and whimsical association.

The p-value of less than 0.01 reaffirms the unlikelihood of this correlation being merely coincidental, akin to stumbling upon a needle in a statistical haystack. This statistical significance adds weight to the unconventional yet intriguing relationship between "Karen" and air pollution, underscoring the need to further explore this unexpected phenomenon with a lighthearted touch amidst the rigors of scientific inquiry.

In conclusion, the findings of this study lend credence to the idea that the name "Karen" has indeed breathed new life into the realm of name-based epidemiology and environmental science. As we navigate the breezy corridors of statistical peculiarities, it becomes apparent that the affair between "Karen" and air pollution in Atlantic City takes center stage, offering a refreshing blend of scholarly whimsy and unexpected correlations.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Karen and Air pollution in Atlantic City, New Jersey. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

[[ABSTRACT]]
This research presents a peculiar analysis of the correlation between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our study uncovers an unexpected relationship between the two seemingly unrelated variables. With a correlation coefficient of 0.9217117 and p < 0.01 from 1980 to 2022, the findings are truly a breath of fresh air in the field of name-based epidemiology and environmental science. Join us as we navigate the winds of change and unveil the curious connection between "Karen" and air pollution, shedding light on this lighthearted yet surprisingly robust association.

[[INTRDUCTION]]
INTRODUCTION
The relationship between human behavior and environmental factors has long been a subject of fascination and conjecture in the fields of epidemiology and environmental science. However, it is not every day that one comes across a connection as unexpected and, dare I say, whimsical, as the one between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. This study delves into the quirkier side of data analysis, where statistical correlations meet social nomenclature to uncover a most unusual relationship.
The first name "Karen" has been the subject of countless memes and jokes in recent years, often associated with a particular stereotype that has permeated popular culture. On the other hand, air pollution, though no laughing matter, has been a persistent environmental concern, especially in urban areas such as Atlantic City. The intersection of these seemingly disparate concepts forms the basis of our investigation.
As we embark on this intellectual escapade, it is imperative to maintain a lighthearted demeanor while interpreting the empirical observations. After all, what better way to spice up the usually somber discourse of air quality research than to introduce a dash of humor and whimsy, wouldn't you agree? The correlation coefficient and p-value may be high, but let us not forget the value of a good pun or two in the pursuit of knowledge!
Join us as we unravel the intrigue behind the "Karen" and air pollution affair, and strive to breathe new life into the world of name-based epidemiology and environmental science. The winds of curiosity are blowing, and we are ready to explore this unexpected and delightful association.

[[RESULTS]]
The results of our analysis revealed a remarkably strong correlation between the popularity of the first name Karen and air pollution in Atlantic City, New Jersey from 1980 to 2022. The correlation coefficient of 0.9217117 suggests a striking relationship, reminiscent of a chance encounter between a gust of wind and a tumbleweed in the desert of statistical probabilities.
With an r-squared value of 0.8495525, it is as if the data points aligned themselves with the precision of a synchronized swimming team, moving in perfect harmony to reveal this unlikely connection. The p-value of less than 0.01 indicates that the likelihood of this association being due to mere chance is about as probable as finding a polar bear in the Sahara desert.
Fig. 1 exhibits a scatterplot illustrating the robust association, with data points resembling constellations in the statistical galaxy, forging an unexpected constellation of "Karen" and air pollution. It is as if the data itself conspired to reveal this peculiar relationship, adding a touch of whimsy to the typically stern field of environmental science.
This unexpected correlation breathes new life into the realm of name-based epidemiology and environmental science, shining a light on the delightful and unconventional intersection between human nomenclature and air quality. It appears that in the arena of statistical peculiarities, the "Karen" and air pollution affair takes center stage, inviting further exploration and a touch of humor amidst the rigors of scientific inquiry.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, this study has successfully unveiled the intriguing relationship between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. The results speak for themselves, echoing through the statistical corridors like a cleverly delivered punchline at a stand-up comedy show. The robust correlation coefficient and r-squared value point to a connection as unmistakable as a cat's disdain for water – an unexpected yet undeniable reality.

The scatterplot not only depicts the association but also paints a picture of statistical serendipity, akin to stumbling upon a four-leaf clover in a field of data points. The findings serve as a reminder that in the enchanting dance of statistics, even the most unlikely pairs can tango with grace and precision, much like a penguin on an ice rink.

The implications of this research extend beyond the realms of science and enter the delightful territory of societal whimsy – a place where playful banter meets rigorous analysis in a riveting tango. It is as if the data itself has decided to don a fancy dress and throw a masquerade ball for the senses, inviting us to partake in this unexpected and delightful revelry.

Therefore, in the grand theater of statistical quirks and serendipities, we assert that no further research is needed in this area. Like a perfectly timed punchline, this study concludes with a resounding note of whimsical finality, leaving no doubt that the "Karen" and air pollution affair is a unique and lighthearted gem in the tapestry of scientific inquiry, eliciting a chuckle and a nod of approval in equal measure.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Quirks and Anomalies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Humorous Environmental Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality with an abstract of This research presents a peculiar analysis of the correlation between the popularity of the first name Karen and air pollution levels in Atlantic City, New Jersey. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our study uncovers an unexpected relationship between the two seemingly unrelated variables. With a correlation coefficient of 0.9217117 and p < 0.01 from 1980 to 2022, the findings are truly a breath of fresh air in the field of name-based epidemiology and environmental science. Join us as we navigate the winds of change and unveil the curious connection between "Karen" and air pollution, shedding light on this lighthearted yet surprisingly robust association.

ChatGPT:

Karen, air pollution, Atlantic City, name-based epidemiology, environmental science, US Social Security Administration, Environmental Protection Agency, correlation coefficient, lighthearted association

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Popularity of the first name Karen
Detailed data title: Babies of all sexes born in the US named Karen
Source: US Social Security Administration
See what else correlates with Popularity of the first name Karen

Air pollution in Atlantic City, New Jersey
Detailed data title: Percentage of days with moderate or worse air quality in Atlantic City-Hammonton, NJ
Source: Environmental Protection Agency
See what else correlates with Air pollution in Atlantic City, New Jersey

Correlation r = 0.9217117 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.8495525 (Coefficient of determination)
This means 85% of the change in the one variable (i.e., Air pollution in Atlantic City, New Jersey) is predictable based on the change in the other (i.e., Popularity of the first name Karen) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-18.^Show 0.0000000000000000018320037382
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.92 in 1.8E-16% of random cases. Said differently, if you correlated 545,850,414,575,316,736 random variables^Note You don't actually need 545 quadrillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 42 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.86, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Karen (Babies born)	5083	4561	4185	3809	3565	3163	2824	2614	2587	2797	2734	2621	2789	2841	2504	2287	2417	2234	2079	2186	2194	2212	2230	2340	2179	2074	2040	2184	1821	1433	1295	1111	901	730	633	631	616	560	469	445	336	229	196
Air pollution in Atlantic City, New Jersey (Bad air quality days)	64.3454	46.3014	37.1105	43.956	40.7104	36.1644	29.7521	31.9767	27.0423	26.8222	26.1364	35.6354	27.0492	30.411	26.5753	29.3151	29.0411	32.6027	31.044	25.7703	23.1844	23.0769	28.2967	23.8356	18.8953	27.5568	26.4624	28.022	30.4709	26.5928	27.3973	22.0056	20.7865	16.6667	8.53994	13.0556	13.7363	15.8904	10.411	10.137	8.07799	10.4972	5.20548

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([5083,4561,4185,3809,3565,3163,2824,2614,2587,2797,2734,2621,2789,2841,2504,2287,2417,2234,2079,2186,2194,2212,2230,2340,2179,2074,2040,2184,1821,1433,1295,1111,901,730,633,631,616,560,469,445,336,229,196,])
array_2 = np.array([64.3454,46.3014,37.1105,43.956,40.7104,36.1644,29.7521,31.9767,27.0423,26.8222,26.1364,35.6354,27.0492,30.411,26.5753,29.3151,29.0411,32.6027,31.044,25.7703,23.1844,23.0769,28.2967,23.8356,18.8953,27.5568,26.4624,28.022,30.4709,26.5928,27.3973,22.0056,20.7865,16.6667,8.53994,13.0556,13.7363,15.8904,10.411,10.137,8.07799,10.4972,5.20548,])
array_1_name = "Popularity of the first name Karen"
array_2_name = "Air pollution in Atlantic City, New Jersey"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Popularity of the first name Karen
Line chart for only Air pollution in Atlantic City, New Jersey
AI-generated correlation image
The spurious research paper: Fair Karens Beware - The Air Pollution Affair: A Quirk in Atlantic City's Air Quality

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Correlation ID: 5462 · Black Variable ID: 2250 · Red Variable ID: 20295


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